Abstract
Mycobacterium tuberculosis infections cause 9 million new tuberculosis cases and 1.5 million deaths annually1. To identify variants conferring risk of tuberculosis, we tested 28.3 million variants identified through whole-genome sequencing of 2,636 Icelanders for association with tuberculosis (8,162 cases and 277,643 controls), pulmonary tuberculosis (PTB) and M. tuberculosis infection. We found association of three variants in the region harboring genes encoding the class II human leukocyte antigens (HLAs): rs557011[T] (minor allele frequency (MAF) = 40.2%), associated with M. tuberculosis infection (odds ratio (OR) = 1.14, P = 3.1 × 10−13) and PTB (OR = 1.25, P = 5.8 × 10−12), and rs9271378[G] (MAF = 32.5%), associated with PTB (OR = 0.78, P = 2.5 × 10−12)—both located between HLA-DQA1 and HLA-DRB1—and a missense variant encoding p.Ala210Thr in HLA-DQA1 (MAF = 19.1%, rs9272785), associated with M. tuberculosis infection (P = 9.3 × 10−9, OR = 1.14). We replicated association of these variants with PTB in samples of European ancestry from Russia and Croatia (P < 5.9 × 10−4). These findings show that the HLA class II region contributes to genetic risk of tuberculosis, possibly through reduced presentation of protective M. tuberculosis antigens to T cells.
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References
World Health Organization. WHO Global Tuberculosis Report 2014, WHO/HTM/TB/2014.08 (World Health Organization, 2014).
Fox, G.J. & Menzies, D. Epidemiology of tuberculosis immunology. Adv. Exp. Med. Biol. 783, 1–32 (2013).
Comstock, G.W. Tuberculosis in twins: a re-analysis of the Prophit survey. Am. Rev. Respir. Dis. 117, 621–624 (1978).
Sigurdsson, S. Tuberculosis in Iceland. 1976. Laeknabladid 91, 69–102 (2005).
Sigurdsson, S. Um berklaveiki á Íslandi. Laeknabladid 62, 3–50 (1976).
Bothamley, G.H., Ditiu, L., Migliori, G.B. & Lange, C. Active case finding of tuberculosis in Europe: a Tuberculosis Network European Trials Group (TBNET) survey. Eur. Respir. J. 32, 1023–1030 (2008).
Gudbjartsson, D.F. et al. Large-scale whole-genome sequencing of the Icelandic population. Nat. Genet. 47, 435–444 (2015).
DePristo, M.A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).
Cobat, A. et al. Two loci control tuberculin skin test reactivity in an area hyperendemic for tuberculosis. J. Exp. Med. 206, 2583–2591 (2009).
Cobat, A. et al. Tuberculin skin test negativity is under tight genetic control of chromosomal region 11p14-15 in settings with different tuberculosis endemicities. J. Infect. Dis. 211, 317–321 (2015).
Emilsson, V. et al. Genetics of gene expression and its effect on disease. Nature 452, 423–428 (2008).
Curtis, J. et al. Susceptibility to tuberculosis is associated with variants in the ASAP1 gene encoding a regulator of dendritic cell migration. Nat. Genet. 47, 523–527 (2015).
Thye, T. et al. Common variants at 11p13 are associated with susceptibility to tuberculosis. Nat. Genet. 44, 257–259 (2012).
Thye, T. et al. Genome-wide association analyses identifies a susceptibility locus for tuberculosis on chromosome 18q11.2. Nat. Genet. 42, 739–741 (2010).
Chimusa, E.R. et al. Genome-wide association study of ancestry-specific TB risk in the South African Coloured population. Hum. Mol. Genet. 23, 796–809 (2014).
Sollid, L.M. Coeliac disease: dissecting a complex inflammatory disorder. Nat. Rev. Immunol. 2, 647–655 (2002).
Sollid, L.M., Qiao, S.W., Anderson, R.P., Gianfrani, C. & Koning, F. Nomenclature and listing of celiac disease relevant gluten T-cell epitopes restricted by HLA-DQ molecules. Immunogenetics 64, 455–460 (2012).
Lundin, K.E.A., Scott, H., Fausa, O., Thorsby, E. & Sollid, L.M. T cells from the small intestinal mucosa of a DR4, DQ7/DR4, DQ8 celiac disease patient preferentially recognize gliadin when presented by DQ8. Hum. Immunol. 41, 285–291 (1994).
Aly, T.A. et al. Extreme genetic risk for type 1A diabetes. Proc. Natl. Acad. Sci. USA 103, 14074–14079 (2006).
Zanelli, E., Breedveld, F.C. & de Vries, R.R. HLA class II association with rheumatoid arthritis: facts and interpretations. Hum. Immunol. 61, 1254–1261 (2000).
Rider, L.G. The heterogeneity of juvenile myositis. Autoimmun. Rev. 6, 241–247 (2007).
Lindestam Arlehamn, C.S., Lewinsohn, D., Sette, A. & Lewinsohn, D. Antigens for CD4 and CD8 T cells in tuberculosis. Cold Spring Harb. Perspect. Med. 4, a018465 (2014).
Lindestam Arlehamn, C.S. & Sette, A. Definition of CD4 immunosignatures associated with MTB. Front. Immunol. 5, 124 (2014).
Arlehamn, C.S. et al. Dissecting mechanisms of immunodominance to the common tuberculosis antigens ESAT-6, CFP10, Rv2031c (hspX), Rv2654c (TB7.7), and Rv1038c (EsxJ). J. Immunol. 188, 5020–5031 (2012).
Miyadera, H., Ohashi, J., Lernmark, Å., Kitamura, T. & Tokunaga, K. Cell-surface MHC density profiling reveals instability of autoimmunity-associated HLA. J. Clin. Invest. 125, 275–291 (2015).
Busch, R. et al. On the perils of poor editing: regulation of peptide loading by HLA-DQ and H2-A molecules associated with celiac disease and type 1 diabetes. Expert Rev. Mol. Med. 14, e15 (2012).
Tollefsen, S. et al. Structural and functional studies of trans-encoded HLA-DQ2.3 (DQA1*03:01/DQB1*02:01) protein molecule. J. Biol. Chem. 287, 13611–13619 (2012).
Yin, L., Maben, Z.J., Becerra, A. & Stern, L.J. Evaluating the role of HLA-DM in MHC class II–peptide association reactions. J. Immunol. 195, 706–716 (2015).
Cho, K.J., Walseng, E., Ishido, S. & Roche, P.A. Ubiquitination by March-I prevents MHC class II recycling and promotes MHC class II turnover in antigen-presenting cells. Proc. Natl. Acad. Sci. USA 112, 10449–10454 (2015).
Chadwick, L.H. The NIH Roadmap Epigenomics Program data resource. Epigenomics 4, 317–324 (2012).
Sheffield, N.C. et al. Patterns of regulatory activity across diverse human cell types predict tissue identity, transcription factor binding, and long-range interactions. Genome Res. 23, 777–788 (2013).
Chapman, S.J. & Hill, A.V. Human genetic susceptibility to infectious disease. Nat. Rev. Genet. 13, 175–188 (2012).
Fernando, M.M. et al. Defining the role of the MHC in autoimmunity: a review and pooled analysis. PLoS Genet. 4, e1000024 (2008).
de Bakker, P.I. et al. A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC. Nat. Genet. 38, 1166–1172 (2006).
Meyer, C.G. & Thye, T. Host genetic studies in adult pulmonary tuberculosis. Semin. Immunol. 26, 445–453 (2014).
Etokebe, G.E. et al. Toll-like receptor 2 (P631H) mutant impairs membrane internalization and is a dominant negative allele. Scand. J. Immunol. 71, 369–381 (2010).
Knezević, J. et al. Heterozygous carriage of a dysfunctional Toll-like receptor 9 allele affects CpG oligonucleotide responses in B cells. J. Biol. Chem. 287, 24544–24553 (2012).
Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).
Styrkarsdottir, U. et al. Nonsense mutation in the LGR4 gene is associated with several human diseases and other traits. Nature 497, 517–520 (2013).
Kutyavin, I.V. et al. A novel endonuclease IV post-PCR genotyping system. Nucleic Acids Res. 34, e128 (2006).
Price, A.L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).
Price, A.L. et al. The impact of divergence time on the nature of population structure: an example from Iceland. PLoS Genet. 5, e1000505 (2009).
Kent, W.J. et al. The human genome browser at UCSC. Genome Res. 12, 996–1006 (2002).
McLaren, W. et al. Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor. Bioinformatics 26, 2069–2070 (2010).
Pruitt, K.D., Tatusova, T., Brown, G.R. & Maglott, D.R. NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy. Nucleic Acids Res. 40, D130–D135 (2012).
Devlin, B. & Roeder, K. Genomic control for association studies. Biometrics 55, 997–1004 (1999).
Holm, S. A simple sequentially rejective multiple test procedure. Scand. J. Stat. 6, 65–70 (1979).
ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).
Davydov, E.V. et al. Identifying a high fraction of the human genome to be under selective constraint using GERP. PLoS Comput. Biol. 6, e1001025 (2010).
Garber, M. et al. Identifying novel constrained elements by exploiting biased substitution patterns. Bioinformatics 25, i54–i62 (2009).
Wang, J. et al. Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors. Genome Res. 22, 1798–1812 (2012).
Ward, L.D. & Kellis, M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 40, D930–D934 (2012).
Acknowledgements
The authors thank the study participants and the staff at the Patient Recruitment Center and the deCODE genetics core facilities. We thank S. Balen (University of Rijeka) and M. Balija (Croatian Institute for Transfusion Medicine) for assistance in the collection of blood samples, S. Grle-Popovic for assistance in collection of blood samples of tuberculosis patients treated at the University Hospital Center, Zagreb, and J. Pavelic (Ruđer Bošković Institute) for providing resources and advice. This work was supported by the US National Institute of Allergy and Infectious Diseases grant HHSN266200400064C (deCODE Genetics, A. Kong, K.G.K., M.G., M.K.), UK Wellcome Trust grants 088838/Z/09/Z and 095198/Z/10/Z (S.N.), EU Framework Programme 7 Collaborative grant 201483 (University of Cambridge and S.N.), European Research Council Starting grant 260477 and Royal Society grants UF0763346 and RG090638 (S.N.). S.N. is also supported by a Wellcome Trust Senior Research fellowship and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre.
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G.S., D.F.G., B.V.H., A. Kong, U.T., T.B., I.J. and K.S. designed the study and interpreted the results. T.B., K.G.K., M.G., L.J.G., A.L., M.K. and K.B. coordinated and managed phenotype data ascertainment and Icelandic subject recruitment. S.N., J.C.B. and Y.L. coordinated, managed, genotyped and analyzed the Russian cohort sample set. L.B.K., J.K. and Z.D. coordinated and managed the Croatian cohort phenotypes and samples, which were genotyped and analyzed by deCODE. G.S., H.T.H., G.M., S.A.G., O.T.M., U.T. and I.J. performed the sequencing, genotyping and expression analyses. G.S., D.F.G., B.V.H., S.A.G., A.G., Adalbjorg Jonasdottir, Aslaug Jonasdottir, A. Karason, H.K. and I.J. performed HLA typing and analysis of HLA data. G.S., D.F.G., B.V.H., A.G., S.A.G., P.S., A. Kong, G.M. and I.J. performed the statistical and bioinformatics analyses. G.S., D.F.G., S.N., I.J. and K.S. drafted the manuscript. All authors contributed to the final version of the manuscript.
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G.S., D.F.G., B.V.H., L.J.G., A.G., S.A.G., H.T.H., Adalbjorg Jonasdottir, Aslaug Jonasdottir, A. Karason, H.K., O.T.M., P.S., A. Kong, G.M., U.T., I.J. and K.S. are employed by deCODE Genetics/Amgen, Inc.
Integrated supplementary information
Supplementary Figure 1 Q-Q plots of tuberculosis GWAS results.
Q-Q plots using uncorrected (red) and corrected (blue, using the method of genomic control) χ2 statistics from the tuberculosis GWAS of pulmonary tuberculosis, all tuberculosis and M. tuberculosis. All P-values below 0.05 are plotted.
Supplementary Figure 2 Principal components plot of cases and controls.
The figure shows first two principal components of the Icelandic cases and controls used in the association. Pulmonary tuberculosis, all tuberculosis and M. tuberculosis infected cases are plotted in blue, and population controls in black.
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Supplementary Text and Figures
Supplementary Figures 1–2, Supplementary Tables 1–6 and 8–12, and Supplementary Note (PDF 1644 kb)
Supplementary Table 7
Association signals of imputed classical HLA alleles with PTB in Iceland. HLA alleles at four digit levels were established using imputation of sequence data from a set of 2,614 whole-genome sequenced individuals (XLSX 38 kb)
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Sveinbjornsson, G., Gudbjartsson, D., Halldorsson, B. et al. HLA class II sequence variants influence tuberculosis risk in populations of European ancestry. Nat Genet 48, 318–322 (2016). https://doi.org/10.1038/ng.3498
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DOI: https://doi.org/10.1038/ng.3498
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